Originally published on dl.acm.org
Proceedings of the 11th ACM SIGPLAN International Workshop on Tools for Automatic Program Analysis, TAPAS@SPLASH 2020, Virtual Event, USA, November 17, 2020
Vineeth Kashyap, Roger Scott, Joseph Ranieri, David Melski and Lucja Kot
Use of third-party library APIs is pervasive, but can be error-prone. API-usage errors can be detected via static analysis if specifications of correct usage are available, but manually creating such specifications is a bottleneck. We showcase a semi-automated “big code” solution, where we use large code corpora to mine patterns in API usage, and ask human experts to perform analytics on those patterns to create static analysis rules.